Lauren’s Home Range Analysis

packages<-c("adehabitatHR","data.table","ggfortify","grid","move","moveVis","OpenStreetMap","pbapply","plotly","rgdal","sp","tidyverse","viridis")
sapply(packages, require, character.only=T)

 adehabitatHR    data.table     ggfortify          grid          move       moveVis OpenStreetMap       pbapply 
         TRUE          TRUE          TRUE          TRUE          TRUE          TRUE          TRUE          TRUE 
       plotly         rgdal            sp     tidyverse       viridis 
         TRUE          TRUE          TRUE          TRUE          TRUE 

data <- read.csv("bats.csv")

Plot 1

qaqc_plot <- ggplot() + geom_point(data=data, 
                                   aes(utm.easting,utm.northing,
                                       color=individual.local.identifier)) +
                        labs(x="Easting", y="Northing") +
                        guides(color=guide_legend("Bat Identifier"))

ggplotly(qaqc_plot)

Plot 2

lapply(split(data, data$individual.local.identifier), 
       function(x)write.csv(x, file = paste(x$individual.local.identifier[1],".csv"), row.names = FALSE))

cannot open file 'Bat 1 .csv': Permission deniedError in file(file, ifelse(append, "a", "w")) : 
  cannot open the connection

files <- c("Bat 5 .csv", "Bat 6 .csv")

utm_points <- cbind(data$utm.easting, data$utm.northing)
utm_locations <- SpatialPoints(utm_points, 
                 proj4string=CRS("+proj=utm +zone=14 +datum=WGS84"))
proj_lat.lon <- as.data.frame(spTransform(
                utm_locations, CRS("+proj=longlat +datum=WGS84")))
colnames(proj_lat.lon) <- c("x","y")
raster <- openmap(c(max(proj_lat.lon$y)+0.01, min(proj_lat.lon$x)-0.01), 
                  c(min(proj_lat.lon$y)-0.01, max(proj_lat.lon$x)+0.01), 
                  type = "bing")
raster_utm <- openproj(raster, 
              projection = "+proj=utm +zone=14 +ellps=WGS84 +units=m +no_defs")

autoplot(raster_utm, expand = TRUE) + theme_bw() +
  theme(legend.position="right") +
  theme(panel.border = element_rect(colour = "black", fill=NA, size=1)) +
  geom_point(data=data, aes(utm.easting,utm.northing,
             color=individual.local.identifier), size = 3, alpha = 0.8) +
  theme(axis.title = element_text(face="bold")) + labs(x="Easting",
        y="Northing") + guides(color=guide_legend("Bat Identifier"))

Plot 3 - Minimum Convex Polygon

mcp_raster <- function(filename){
  data <- read.csv(file = filename)
  x <- as.data.frame(data$utm.easting)
  y <- as.data.frame(data$utm.northing)
  xy <- c(x,y)
  data.proj <- SpatialPointsDataFrame(xy,data, proj4string = CRS("+proj=utm +zone=14 +ellps=WGS84 +units=m +no_defs"))
  xy <- SpatialPoints(data.proj@coords)
  mcp.out <- mcp(xy, percent=100, unout="ha")
  mcp.points <- cbind((data.frame(xy)),data$individual.local.identifier)
  colnames(mcp.points) <- c("x","y", "identifier")
  mcp.poly <- fortify(mcp.out, region = "id")
  units <- grid.text(paste(round(mcp.out@data$area,2),"ha"), x=0.85,  y=0.95,
                     gp=gpar(fontface=4, col="white", cex=0.9), draw = FALSE)
  mcp.plot <- autoplot(raster_utm, expand = TRUE) + theme_bw() + theme(legend.position="none") +
    theme(panel.border = element_rect(colour = "black", fill=NA, size=1)) +
    geom_polygon(data=mcp.poly, aes(x=mcp.poly$long, y=mcp.poly$lat), alpha=0.8) +
    geom_point(data=mcp.points, aes(x=x, y=y)) + 
    labs(x="Easting (m)", y="Northing (m)", title=mcp.points$identifier) +
    theme(legend.position="none", plot.title = element_text(face = "bold", hjust = 0.5)) + 
    annotation_custom(units)
  mcp.plot
}

pblapply(files, mcp_raster)

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Plot 4 - Kernel-Density Estimation

kde_raster <- function(filename){
  data <- read.csv(file = filename)
  x <- as.data.frame(data$utm.easting)
  y <- as.data.frame(data$utm.northing)
  xy <- c(x,y)
  data.proj <- SpatialPointsDataFrame(xy,data, proj4string = CRS("+proj=utm +zone=14 +ellps=WGS84 +units=m +no_defs"))
  xy <- SpatialPoints(data.proj@coords)
  kde<-kernelUD(xy, h="href", kern="bivnorm", grid=100)
  ver <- getverticeshr(kde, 95)
  kde.points <- cbind((data.frame(data.proj@coords)),data$individual.local.identifier)
  colnames(kde.points) <- c("x","y","identifier")
  kde.poly <- fortify(ver, region = "id")
  units <- grid.text(paste(round(ver$area,2)," ha"), x=0.85,  y=0.95,
                     gp=gpar(fontface=4, col="white", cex=0.9), draw = FALSE)
  kde.plot <- autoplot(raster_utm, expand = TRUE) + theme_bw() + theme(legend.position="none") +
    theme(panel.border = element_rect(colour = "black", fill=NA, size=1)) +
    geom_polygon(data=kde.poly, aes(x=kde.poly$long, y=kde.poly$lat), alpha = 0.8) +
    geom_point(data=kde.points, aes(x=x, y=y)) +
    labs(x="Easting (m)", y="Northing (m)", title=kde.points$identifier) +
    theme(legend.position="none", plot.title = element_text(face = "bold", hjust = 0.5)) + 
    annotation_custom(units)
  kde.plot
}

pblapply(files, kde_raster)

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Plot 5 - Brownian Bridge Movement

date <- as.POSIXct(strptime(as.character(bat5$timestamp),"%Y-%m-%d %H:%M:%S"))
bat5$date <- date
bat5.reloc <- cbind.data.frame(bat5$utm.easting, bat5$utm.northing,
                                as.vector(bat5$individual.local.identifier),
                                as.POSIXct(date))
colnames(bat5.reloc) <- c("x","y","id","date")
trajectory <- as.ltraj(bat5.reloc, date=date, id="bat5")
sig1 <- liker(trajectory, sig2 = 58, rangesig1 = c(0, 5), plotit = FALSE)
bats.traj <- kernelbb(trajectory, sig1 = .7908, sig2 = 58, grid = 100)
bb_ver <- getverticeshr(bats.traj, 95)
bb_poly <- fortify(bb_ver, region = "id", 
                   proj4string = CRS("+proj=utm +zone=14+
                                     ellps=WGS84 +units=m +no_defs"))
colnames(bb_poly) <- c("x","y","order","hole","piece","id","group")
bb_image <- crop(bats.traj, bb_ver, 
                 proj4string = CRS("+proj=utm +zone=14 +
                                   ellps=WGS84 +units=m +no_defs"))
bb_units <- grid.text(paste(round(bb_ver$area,2)," ha"), x=0.85,  y=0.95,
                   gp=gpar(fontface=4, col="white", cex=0.9), draw = FALSE)
bb.plot <- autoplot(raster_utm, expand = TRUE) + theme_bw() + theme(legend.position="none") +
  theme(panel.border = element_rect(colour = "black", fill=NA, size=1)) +
  geom_tile(data=bb_image, 
            aes(x=bb_image@coords[,1], y=bb_image@coords[,2],
            fill = bb_image@data$ud)) +
  geom_polygon(data=bb_poly, aes(x=x, y=y, group = group), color = "black", fill = NA) +
  scale_fill_viridis_c(option = "inferno") + annotation_custom(bb_units) +
  labs(x="Easting (m)", y="Northing (m)", title="bat5") +
  theme(legend.position="none", plot.title = element_text(face = "bold", hjust = 0.5))
bb.plot

Animated Gif of Movement

bats.move <- move(x=bat5$location.long, 
             y=bat5$location.lat, 
             time=as.POSIXct(bat5$timestamp, 
                             format="%Y-%m-%d %H:%M:%S"), 
             proj=CRS("+proj=longlat +ellps=WGS84 +datum=WGS84"),
             data=bat5, animal=bat5$individual.local.identifier, 
             sensor=bat5$sensor.type)

movement <- align_move(bats.move, res = "max", digit = 0, unit = "secs")

frames <- frames_spatial(movement, path_colours = "red",
                         map_service = "osm", 
                         alpha = 0.5) %>% 
  add_labels(x = "Longitude", y = "Latitude") %>%
  add_northarrow() %>% 
  add_scalebar() %>% 
  add_timestamps(movement, type = "label") %>% 
  add_progress()

Processing movement data...
Approximated animation duration: ≈ 1.48s at 25 fps for 37 frames

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Assigning raster maps to frames...

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Creating frames...

animate_frames(frames, fps = 5, overwrite = TRUE,
               out_file = "./moveVis-5fps.gif")

Rendering animation...
Approximated animation duration: ≈ 7.4s at 5 fps for 37 frames

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